An investigation into the pressure effects on gas detection by spectroscopy method using an integrating sphere as multipass gas absorption cell

International audienceIn recent years, an unusual application of standard integrating sphere has been employed to act as a compact multipass gas absorption cell spectroscopy. This system shows several interests, especially to improve limits of detection thanks to the pressure parameter. In this study, we have modeled the global effects of pressure parameter on absorption measurements. We have tested and compared our simulations by measuring the optical absorption of oxygen under different pressure. The experimental data obtained are in agreement with the simulated results and are discussed in this paper

Data on near infrared polarization spectroscopy measurements to evaluate the potential of the Mueller matrix elements in characterization of turbid liquid samples

In this article, a set of 50 turbid liquid samples with different levels of absorption and scattering properties were prepared and measured at various orientations of polarizers and analyzers to obtain the 16 elements of the complete Muller matrix. Partial Least Square (PLS) was used to build calibration models in order to assess the potential of polarization spectroscopy through the elements of Muller matrix to predict chemical and physical parameters

An investigation into the effects of pressure on gas detection using an integrating sphere as multipass gas absorption cell: analysis and discussion

International audienceThe approach adopted in the present work was to increase the pressure within an integrating sphere system to increase the number density of molecules in the gas cell and hence to obtain a significant absorption in order to improve the sensitivity of the measurement system. This feasibility study has allowed an assessment of the net absorption gain with the rise of pressure and highlights the validity domain of the linear operating regime relative to Beer's law. Experiments were conducted on the oxygen A-band. The absorption peaks of oxygen at 760 nm typically were measured with a 50 mm diameter integrating sphere system under various pressures. Tests were performed up to 200 bar, the pressure for which the linear regime was operative, and analysed from a theoretical and experimental point of view. An experimental net absorption gain of 160 was achieved in this pressure range with the possibility of up to 650 bar while remaining in the linear regime. Finally, the experimental data obtained, in particular the absorption evolution due to the contribution of oxygen gas, seem consistent with the simulated results and are discussed in this paper

Nouvelle méthode optique couplant la polarisation de la lumière avec la spectrométrie proche infrarouge pour améliorer la qualité du signal d'absorbance mesuré sur des sols.

International audienceVisible - Near-infrared spectroscopy (Vis-NIRS) is now commonly used to measure different physical and chemical parameters of soils, including carbon content. However, prediction model accuracy is insufficient for Vis-NIRS to replace routine laboratory analysis. One of the biggest issues this technique is facing up to is light scattering due to soil particles. It causes departure in the assumed linear relationship between the Absorbance spectrum and the concentration of the chemicals of interest as stated by Beer-Lambert’s Law, which underpins the calibration models. Therefore it becomes essential to improve the metrological quality of the measured signal in order to optimize calibration as light/matter interactions are at the basis of the resulting linear modeling. Optics can help to mitigate scattering effect on the signal. We put forward a new optical setup coupling linearly polarized light with a Vis-NIR spectrometer to free the measured spectra from multi-scattering effect. The corrected measured spectrum was then used to compute an Absorbance spectrum of the sample, using Dahm’s Equation in the frame of the Representative Layer Theory. This method has been previously tested and validated on liquid (milk+ dye) and powdered (sand + dye) samples showing scattering (and absorbing) properties. The obtained Absorbance was a very good approximation of the Beer-Lambert’s law absorbance. Here, we tested the method on a set of 54 soil samples to predict Soil Organic Carbon content. In order to assess the signal quality improvement by this method, we built and compared calibration models using Partial Least Square (PLS) algorithm. The prediction model built from new Absorbance spectrum outperformed the model built with the classical Absorbance traditionally obtained with Vis-NIR diffuse reflectance. This study is a good illustration of the high influence of signal quality on prediction model’s performances

Estimation de la teneur en eau et en matière sèche d'une feuille basée sur le transfert radiatif et l'imagerie hyperspectrale NIR

International audienceHyperspectral imaging has become an interesting non-destructive way to spatially characterize various materials such as vegetation. Because several leaf biochemical compounds affect the visible and near-infrared reflectance, they can potentially be retrieved from the measured spectral profile. At leaf scale, usual methods are either statistically- or physically-based. On the one hand, statistical methods aim at extracting a statistical relationship between spectral data and targeted variable(s), thus potentially requiring the construction of a large calibration database to get to an acceptable robustness. On the other hand, physically-based methods use the knowledge of leaf optical properties to retrieve the targeted variables without any calibration. Although being highly effective in ideal laboratory conditions, these methods do not scale well to the close range remote sensing case because they require the signal to be measured in every direction using an integrating sphere. In this study, we propose an improvement of a physically -based model that overcomes the need for multi-angle measurements. This model is then applied to the retrieval of water and dry matter contents from NIR hyperspectral images. This method is based on the PROSPECT radiative transfer model that has been much used to characterize the relationship between the directional-hemispherical reflectance of monocotyledon and dicotyledon species and their biochemical content at leaf level. However, because PROSPECT simulates the sum of both specular and diffuse reflected fluxes over the whole hemisphere, it cannot directly be applied to hyperspectral images of leaves. Using a single light source assumed to be directional, we show that adding two parameters to the PROSPECT model enables the model to be used with hyperspectral measurements. The first parameter is a multiplicative term that is related to local leaf angle and illumination zenith angle. The second parameter is an additive specular-related term that models surface bidirectional effects. The resulting enhanced PROSPECT-based model can therefore be inverted from hyperspectral measurements to retrieve the foliar content, surface effects and leaf local topography. We tested this method on seven leaf species with images acquired in laboratory using a SWIR (1-2.5 µm) hyperspectral camera. Each leaf was imaged in three positions corresponding to average incident angles of 10°, 30° and 50°. Lighting was provided by a collimated halogen source positioned close to the camera. After each image acquisition, water and dry matter contents were evaluated using destructive measurements as these PROSPECT variables have the greatest influence on reflectance in this spectral range. When tested on horizontal leaves, our model accurately retrieved water (R²=0.98,RMSE=24%) and dry matter (R²=0.85,RMSE=16%) contents. Results obtained with both flat and tilted leaves did not show significant decrease in performance, either for water (R²=0.95,RMSE=28%) or dry matter (R²=0.84,RMSE=17%) contents. These results were better than those obtained with PROSPECT alone, i.e., R²=0.79 and RMSE=28% for water content, and R²=0.67 and RMSE=26% for dry matter content. In addition, the estimated spatial distribution of model parameters was clearly not affected by variable surface effects and leaf local topography, thus proving the relevance of the proposed model for hyperspectral imaging compared to original PROSPECT

Cartographie du contenu foliaire basée sur le transfert radiatif et l'imagerie hyperspectrale de proxidétection dans le domaine VIS-NIR

International audienceMost methods for retrieving foliar content from hyperspectral data are well adapted either to remote-sensing scale, for which each spectral measurement has a spatial resolution ranging from a few dozen centimeters to a few hundred meters, or to leaf scale, for which an integrating sphere is required to collect the spectral data. In this study, we present a method for estimating leaf optical properties from hyperspectral images having a spatial resolution of a few millimeters or centimeters. In presence of a single light source assumed to be directional, it is shown that leaf hyperspectral measurements can be related to the directional hemispherical reflectance simulated by the PROSPECT radiative transfer model using two other parameters. The first one is a multiplicative term that is related to local leaf angle and illumination zenith angle. The second parameter is an additive specular-related term that models BRDF effects.Our model was tested on visible and near infrared hyperspectral images of leaves of various species, that were acquired under laboratory conditions. Introducing these two additional parameters into the inversion scheme leads to improved estimation results of PROSPECT parameters when compared to original PROSPECT. In particular, the RMSE for local chlorophyll content estimation was reduced by 21% (resp. 32%) when tested on leaves placed in horizontal (resp. sloping) position. Furthermore, inverting this model provides interesting information on local leaf angle, which is a crucial parameter in classical remote-sensing